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The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study

For controlling recent COVID-19 outbreaks around the world, many countries have implemented suppression and mitigation interventions. This work aims to conduct a feasibility study for accessing the effect of multiple interventions to control the COVID-19 breakouts in the UK and other European countr...

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Autores principales: Yang, Po, Yang, Geng, Qi, Jun, Sheng, Bin, Yang, Yun, Zhang, Shuhao, Bi, Gaoshan, Mao, Xuxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862317/
https://www.ncbi.nlm.nih.gov/pubmed/33542294
http://dx.doi.org/10.1038/s41598-021-82170-y
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author Yang, Po
Yang, Geng
Qi, Jun
Sheng, Bin
Yang, Yun
Zhang, Shuhao
Bi, Gaoshan
Mao, Xuxin
author_facet Yang, Po
Yang, Geng
Qi, Jun
Sheng, Bin
Yang, Yun
Zhang, Shuhao
Bi, Gaoshan
Mao, Xuxin
author_sort Yang, Po
collection PubMed
description For controlling recent COVID-19 outbreaks around the world, many countries have implemented suppression and mitigation interventions. This work aims to conduct a feasibility study for accessing the effect of multiple interventions to control the COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand. The model is to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK, with two features considered: direct link between exposed and recovered population, and practical healthcare demand by separation of infections. We combined the calibrated model with COVID-19 data in London and non-London regions in the UK during February and April 2020. Our finding suggests that rolling intervention is an optimal strategy to effectively control COVID-19 outbreaks in the UK for balancing healthcare demand and morality ratio. It is better to implement regional based interventions with varied intensities and maintenance periods. We suggest an intervention strategy named as “Besieged and rolling interventions” to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK.
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spelling pubmed-78623172021-02-05 The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study Yang, Po Yang, Geng Qi, Jun Sheng, Bin Yang, Yun Zhang, Shuhao Bi, Gaoshan Mao, Xuxin Sci Rep Article For controlling recent COVID-19 outbreaks around the world, many countries have implemented suppression and mitigation interventions. This work aims to conduct a feasibility study for accessing the effect of multiple interventions to control the COVID-19 breakouts in the UK and other European countries, accounting for balance of healthcare demand. The model is to infer the impact of mitigation, suppression and multiple rolling interventions for controlling COVID-19 outbreaks in the UK, with two features considered: direct link between exposed and recovered population, and practical healthcare demand by separation of infections. We combined the calibrated model with COVID-19 data in London and non-London regions in the UK during February and April 2020. Our finding suggests that rolling intervention is an optimal strategy to effectively control COVID-19 outbreaks in the UK for balancing healthcare demand and morality ratio. It is better to implement regional based interventions with varied intensities and maintenance periods. We suggest an intervention strategy named as “Besieged and rolling interventions” to the UK that take a consistent suppression in London for 100 days and 3 weeks rolling intervention in other regions. This strategy would reduce the overall infections and deaths of COVID-19 outbreaks, and balance healthcare demand in the UK. Nature Publishing Group UK 2021-02-04 /pmc/articles/PMC7862317/ /pubmed/33542294 http://dx.doi.org/10.1038/s41598-021-82170-y Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Yang, Po
Yang, Geng
Qi, Jun
Sheng, Bin
Yang, Yun
Zhang, Shuhao
Bi, Gaoshan
Mao, Xuxin
The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title_full The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title_fullStr The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title_full_unstemmed The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title_short The effect of multiple interventions to balance healthcare demand for controlling COVID-19 outbreaks: a modelling study
title_sort effect of multiple interventions to balance healthcare demand for controlling covid-19 outbreaks: a modelling study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862317/
https://www.ncbi.nlm.nih.gov/pubmed/33542294
http://dx.doi.org/10.1038/s41598-021-82170-y
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